Data Scientist

TechDigital Group; Santa Clara (CA); On-site; USD 90,000 - 150,000; Full time

Job summary

An established industry player is seeking a Data Scientist with a robust background in AI and deep learning. This role involves leveraging your strong programming skills in Python to design and optimize large language models and natural language processing systems. You'll work with complex datasets and apply advanced techniques in supervised and unsupervised learning, reinforcement learning, and more. If you're passionate about AI and thrive in cloud environments, this is an exciting opportunity to contribute to cutting-edge projects and advance your career in a dynamic and innovative setting.

Qualifications

• 6+ years of IT experience with 3+ years in Data Science.
• Hands-on AI modeling experience with complex datasets.

Responsibilities

• Design and optimize LLM and NLP systems independently.
• Build RAG applications using open-source LLM models.

Skills

Python Programming

Supervised Learning

Unsupervised Learning

Deep Learning

Reinforcement Learning

Federated Learning

Time Series Forecasting

Bayesian Statistics

Optimization

Education

B.E. or B. Tech in Computer Science

M. Tech or MCA in Computer Science

Tools

TensorFlow

PyTorch

AWS

Azure

GCP

Databricks

Job description

B.E. B. Tech M. Tech/ MCA in computer science, artificial intelligence, or a related field.

6+ years of IT experience with a minimum of 3+ years in Data Science (AI/Client).

Strong programming skills in Python.

Experience with deep learning frameworks (e.g., TensorFlow, PyTorch).

Hands-on AI/Client modeling experience of complex datasets combined with a strong understanding of the theoretical foundations of AI/Client (Research Oriented).

Expertise in most of the following areas:

1. Supervised learning
2. Unsupervised learning
3. Deep learning
4. Reinforcement learning
5. Federated learning
6. Time series forecasting
7. Bayesian statistics
8. Optimization

Hands-on experience in designing and optimizing LLM, natural language processing (NLP) systems, frameworks, and tools.

Building RAG applications independently using available open-source LLM models.

Comfortable working in cloud and high-performance computing environments (e.g., AWS/Azure/GCP, Databricks).